Methods, apparatus and systems for determining a transport block size in a wireless communication

ABSTRACT

Methods, apparatus and systems for determining a transport block size in a wireless communication are disclosed. In one embodiment, a method performed by a wireless communication device is disclosed. The method comprises: receiving control information from a wireless communication node, wherein the control information includes a plurality of transmission parameters related to transport blocks to be transmitted between the wireless communication device and the wireless communication node; calculating an intermediate transport block size (TBS) for the transport blocks based on the plurality of transmission parameters; modifying the intermediate TBS to generate a modified TBS in response to an event that the intermediate TBS is smaller than a threshold; and determining a final TBS for the transport blocks based on a TBS that is closest to the modified TBS, among TBSs that are in a quantized set and not smaller than the modified TBS.

CROSS-REFERENCE TO RELATED APPLICATION

The present application claims priority to PCT international applicationPCT/CN2017/111730, entitled “METHODS, APPARATUS AND SYSTEMS FORDETERMINING A TRANSPORT BLOCK SIZE IN A WIRELESS COMMUNICATION,” filedon Nov. 17, 2017, which is expressly incorporated by reference herein inits entirety.

TECHNICAL FIELD

The disclosure relates generally to wireless communications and, moreparticularly, to methods, apparatus and systems for determining atransport block size in a wireless communication.

BACKGROUND

Wireless networking systems have become a prevalent means by which amajority of people worldwide has come to communicate. A typical wirelesscommunication network (e.g., employing frequency, time, and/or codedivision techniques) includes one or more base stations (typically knownas a “BS”) that each provides a geographical radio coverage, and one ormore wireless user equipment devices (typically know as a “UE”) that cantransmit and receive data within the radio coverage.

In a wireless communication system, e.g. the fifth-generation (5G) newradio (NR) network, a transport block (TB) is usually encoded and thensent. The UE obtains the modulation order, code rate and the number oflayers from the downlink control information (DCI) and can calculate thenumber of resource elements from the allocated time and frequency domainranges in the DCI. The UE can obtain an intermediate transport blocksize (TBS) based on these transmission parameters and determine theactual transmitted TBS according to a requirement of channel coding.Coding gains are different for different transport block sizes.Generally, a smaller transport block can obtain a coding gain smallerthan that obtained by a larger transport block. But when the size of thetransport block exceeds a certain value, the increase of coding gain isnot obvious.

In an existing system, the transport block size (TBS) is calculatedthrough a formula, wherein when the number of physical resource blocks(PRBs) is smaller, and when the level of modulation and coding scheme(MCS) is lower, the TBS is smaller and the performance of the resultingsmall transport block is poor. That is, to achieve the same target blockerror rate (BLER), a signal-to-noise ratio (SNR) required for a smallertransport block is higher than an SNR required for a large transportblock. Therefore, when the calculated TBS is small, once the TBSslightly deviates from the actual TBS that can be transmitted, the SNRrequired to reach the same target BLER is greatly changed, which causesan unstable link performance.

In addition, the TBS calculated under different modulation orders andthe SNR required to achieve the same target BLER follow some rules in anMCS table. When the number of PRBs is constant and the modulation orderis constant, the value of SNR increases with the increase of spectrumefficiency (SE) or code rate (CR). In addition, the SNR change, referredto as ΔSNR, of adjacent MCSs is balanced with the SE change, referred toas ΔSE, of the adjacent MCSs. But in an actual MCS table, in order toensure the same spectrum efficiency of adjacent MCSs of differentmodulation orders, it may result in a non-uniform distribution of ΔSEvalues of adjacent MCSs of the same modulation order, which leads to anon-uniform ΔSNR value of at the modulation order hopping, and againimpacting the stability of the link.

Further, for any number of PRBs and any MCS modulation order, after theTBS is calculated by using an existing formula, if any one of theparameters in the formula changes, the calculated TBS will change.Because the two calculated TBSs during an initial transmission and aretransmission may be different, the transmission cannot be continued.

Thus, existing systems and methods for determining a transport blocksize in a wireless communication are not entirely satisfactory.

SUMMARY OF THE INVENTION

The exemplary embodiments disclosed herein are directed to solving theissues relating to one or more of the problems presented in the priorart, as well as providing additional features that will become readilyapparent by reference to the following detailed description when takenin conjunction with the accompany drawings. In accordance with variousembodiments, exemplary systems, methods, devices and computer programproducts are disclosed herein. It is understood, however, that theseembodiments are presented by way of example and not limitation, and itwill be apparent to those of ordinary skill in the art who read thepresent disclosure that various modifications to the disclosedembodiments can be made while remaining within the scope of the presentdisclosure.

In one embodiment, a method performed by a wireless communication deviceis disclosed. The method comprises: receiving control information from awireless communication node, wherein the control information includes aplurality of transmission parameters related to transport blocks to betransmitted between the wireless communication device and the wirelesscommunication node; calculating an intermediate transport block size(TBS) for the transport blocks based on the plurality of transmissionparameters; modifying the intermediate TBS to generate a modified TBS inresponse to an event that the intermediate TBS is smaller than athreshold; and determining a final TBS for the transport blocks based ona TBS that is closest to the modified TBS, among TBSs that are in aquantized set and not smaller than the modified TBS.

In a further embodiment, a method performed by a wireless communicationnode is disclosed. The method comprises: generating a plurality oftransmission parameters related to transport blocks; transmittingcontrol information that comprises the plurality of transmissionparameters; calculating an intermediate transport block size (TBS) forthe transport blocks based on the plurality of transmission parameters;modifying the intermediate TBS to generate a modified TBS in response toan event that the intermediate TBS is smaller than a threshold;determining a final TBS for the transport blocks based on a TBS that isclosest to the modified TBS, among TBSs that are in a quantized set andnot smaller than the modified TBS; and communicating with a wirelesscommunication device using the transport blocks based on the final TBS.

In a different embodiment, a wireless communication device configured tocarry out a disclosed method in some embodiment is disclosed.

In yet another embodiment, a wireless communication node configured tocarry out a disclosed method in some embodiment is disclosed.

In still another embodiment, a non-transitory computer-readable mediumhaving stored thereon computer-executable instructions for carrying outa disclosed method in some embodiment is disclosed.

BRIEF DESCRIPTION OF THE DRAWINGS

Various exemplary embodiments of the present disclosure are described indetail below with reference to the following Figures. The drawings areprovided for purposes of illustration only and merely depict exemplaryembodiments of the present disclosure to facilitate the reader'sunderstanding of the present disclosure. Therefore, the drawings shouldnot be considered limiting of the breadth, scope, or applicability ofthe present disclosure. It should be noted that for clarity and ease ofillustration these drawings are not necessarily drawn to scale.

FIG. 1A illustrates an exemplary communication network in whichtechniques disclosed herein may be implemented, in accordance with anembodiment of the present disclosure.

FIG. 1B illustrates an exemplary simulation result of link stabilitychange vs. modulation and coding scheme (MCS) index, in accordance withan embodiment of prior art.

FIG. 1C illustrates an exemplary simulation result of signal-to-noiseratio (SNR) performance change vs. MCS index, in accordance with anembodiment of prior art.

FIG. 2 illustrates a block diagram of a user equipment (UE), inaccordance with some embodiments of the present disclosure.

FIG. 3 illustrates a flow chart for a method performed by a UE fordetermining a transport block size in a wireless communication, inaccordance with some embodiments of the present disclosure.

FIG. 4 illustrates a block diagram of a base station (BS), in accordancewith some embodiments of the present disclosure.

FIG. 5 illustrates a flow chart for a method performed by a BS fordetermining a transport block size in a wireless communication, inaccordance with some embodiments of the present disclosure. index, inaccordance with an embodiment of the present disclosure.

FIG. 6B illustrates an exemplary simulation result of SNR performancechanges vs. MCS index, in accordance with an embodiment of the presentdisclosure.

FIG. 7A illustrates another exemplary simulation result of linkstability changes vs. MCS index, in accordance with an embodiment of thepresent disclosure.

FIG. 7B illustrates another exemplary simulation result of SNRperformance changes vs. MCS index, in accordance with an embodiment ofthe present disclosure.

FIG. 8A illustrates yet another exemplary simulation result of linkstability changes vs. MCS index, in accordance with an embodiment of thepresent disclosure.

FIG. 8B illustrates yet another exemplary simulation result of SNRperformance changes vs. MCS index, in accordance with an embodiment ofthe present disclosure.

FIG. 9 illustrates a different exemplary simulation result of SNRperformance changes vs. MCS index, in accordance with an embodiment ofthe present disclosure.

FIG. 10A illustrates an exemplary distribution of unquantized TBS, inaccordance with an embodiment of the present disclosure.

FIG. 10B illustrates an exemplary distribution of quantized TBS, inaccordance with an embodiment of the present disclosure.

FIG. 11A illustrates another exemplary distribution of unquantized TBS,in accordance with an embodiment of the present disclosure.

FIG. 11B illustrates another exemplary distribution of quantized TBS, inaccordance with an embodiment of the present disclosure.

FIG. 12A illustrates yet another exemplary distribution of unquantizedIBS, in accordance with an embodiment of the present disclosure.

FIG. 12B illustrates yet another exemplary distribution of quantizedTBS, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

Various exemplary embodiments of the present disclosure are describedbelow with reference to the accompanying figures to enable a person ofordinary skill in the art to make and use the present disclosure. Aswould be apparent to those of ordinary skill in the art, after readingthe present disclosure, various changes or modifications to the examplesdescribed herein can be made without departing from the scope of thepresent disclosure. Thus, the present disclosure is not limited to theexemplary embodiments and applications described and illustrated herein.Additionally, the specific order and/or hierarchy of steps in themethods disclosed herein are merely exemplary approaches. Based upondesign preferences, the specific order or hierarchy of steps of thedisclosed methods or processes can be re-arranged while remaining withinthe scope of the present disclosure. Thus, those of ordinary skill inthe art will understand that the methods and techniques disclosed hereinpresent various steps or acts in a sample order, and the presentdisclosure is not limited to the specific order or hierarchy presentedunless expressly stated otherwise.

In a wireless communication system, e.g. the fifth-generation (5G) newradio (NR) network, a transport block (TB) is usually encoded and thensent. Coding gains are different for different transport block sizes.Generally, a smaller transport block can obtain a coding gain smallerthan that obtained by a larger transport block. The coding gain of atransport block having a length of 100 bits may be nearly 1 dB differentfrom that of a transport block having a length of about 5000 bits. Butwhen the size of the transport block exceeds a certain value (forexample, 5000 bits), the increase of coding gain is not obvious.

In an existing system, the transport block size (TBS) is calculatedthrough a formula, wherein the TBS is smaller when the number ofphysical resource blocks (PRBs) is smaller, and when the level ofmodulation and coding scheme (MCS) is lower. The TBS is larger, when thenumber of PRBs is larger and/or when the MCS level is higher. Thus, whenthe number of PRBs is smaller, and when the MCS level is lower, theperformance of the resulting small transport block is poor. That is, toachieve the same target block error rate (BLER), a signal-to-noise ratio(SNR) required for a smaller transport block is higher than an SNRrequired for a large transport block. Therefore, when the calculated TBSis small, once the TBS slightly deviates from the actual TBS that can betransmitted, the SNR required to reach the same target BLER is greatlychanged, which is not conducive to obtaining a stable link performance.In an MCS table, the TBS calculated under different modulation ordersand the SNR required to achieve the same target BLER follow some rulesor trends. When the number of PRBs is constant and the modulation orderis constant, the value of SNR increases with the increase of spectrumefficiency (SE) or code rate (CR). In addition, the SNR change, referredto as ΔSNR, of adjacent MCSs is balanced with the SE change, referred toas ΔSE, of the adjacent MCSs. That is, if the difference between thevalues of ΔSE of adjacent MCSs of the same modulation order is notsignificant (for example, the difference between ΔSEs does not exceed0.05), the ΔSNR value of the adjacent MCSs is relatively uniform, andthe corresponding link stability is also better. But in an actual MCStable, in order to ensure the same spectrum efficiency of adjacent MCSsof different modulation orders, it may result in a non-uniformdistribution of ΔSE values of adjacent MCSs of the same modulationorder, which leads to a non-uniform ΔSNR value of at the modulationorder hopping (where the modulation order changes from an MCS index toan adjacent MCS index in the MCS table), affecting the stability of thelink.

Below is an exemplary MCS table with spectral efficiency analysis:

MCS Table Modulation MCS Index Order TBS Index SE ΔSE 0 2 0 0.2344 NaN 12 1 0.3057 0.0713 2 2 2 0.377 0.0713 3 2 3 0.4893 0.1123 4 2 4 0.60160.1123 5 2 5 0.7393 0.1377 6 2 6 0.877 0.1377 7 2 7 1.0264 0.1494 8 2 81.1758 0.1494 9 2 9 1.3262 0.1504 10 4 9 1.3262 0 11 4 10 1.4766 0.150412 4 11 1.69535 0.21875 13 4 12 1.9141 0.21875 14 4 13 2.1602 0.2461 154 14 2.4063 0.2461 16 4 15 2.5684 0.1621 17 6 15 2.5684 0 18 6 16 2.73050.1621 19 6 17 3.0264 0.2959 20 6 18 3.3223 0.2959 21 6 19 3.6123 0.2922 6 20 3.9023 0.29 23 6 21 4.21285 0.31055 24 6 22 4.5234 0.31055 25 623 4.8193 0.2959 26 6 24 5.1152 0.2959 27 6 25 5.33495 0.21975 28 6 265.5547 0.21975

In response to this problem, the present disclosure provides a method todetermine the size of the transport block. This method modifies theexisting TBS calculation by introducing a correction factor to achievethe purpose of enhancing link stability.

Further, for any number of PRBs and any MCS modulation order, after theTBS is calculated by using the formula, if any one of the parameters inthe formula changes, the calculated TBS will change. For example, theparameters allocated during the initial transmission are: Q_(m)=2,R=308/1024, the number of PRB is 2, the number of REs per PRB is 132,and the TBS is 120. Then the parameters allocated for retransmissionare: Q_(m)=2, R=379/1024, the number of PRB is 2, the number of REs perPRB is 132, and the TBS is 176. Because the two calculated TBSs aredifferent, the transmission cannot be continued.

In response to this problem, in consideration that the transport blocksize is the same during initial transmission and retransmission, thepresent disclosure provides a method to quantize the TBS to obtain a TBSset or TBS table. The UE can select, in the TBS table, a TBS that isclosest to the calculated TBS in terms of rounding, rounding up, orrounding down the calculated TBS, to be a TBS used for transmission. Asthe quantization step size increases with the increase of TBS, thedisclosed method can avoid complicated online calculation, ensure thatthe TBS granularity for transmission is good, and ensure that the TBS isthe same in initial transmission and retransmission.

The methods disclosed in the present teaching can be implemented in awireless communication network, where a BS and a UE can communicate witheach other via a communication link, e.g., via a downlink radio framefrom the BS to the UE or via an uplink radio frame from the UE to theBS. In various embodiments, a BS in the present disclosure can include,or be implemented as, a next Generation Node B (gNB), an E-UTRAN Node B(eNB), a Transmission/Reception Point (TRP), an Access Point (AP), etc.;while a UE in the present disclosure can include, or be implemented as,a mobile station (IVIS), a station (STA), etc. A BS and a UE may bedescribed herein as non-limiting examples of “wireless communicationnodes,” and “wireless communication devices” respectively, which canpractice the methods disclosed herein and may be capable of wirelessand/or wired communications, in accordance with various embodiments ofthe present disclosure.

FIG. 1A illustrates an exemplary communication network 100 in whichtechniques disclosed herein may be implemented, in accordance with anembodiment of the present disclosure. As shown in FIG. 1A, the exemplarycommunication network 100 includes a base station (BS) 101 and aplurality of UEs, UE1 110, UE2 120 . . . UE3 130, where the BS 101 cancommunicate with the UEs according to some wireless protocols. Forexample, before a downlink transmission, the BS 101 transmits downlinkcontrol information (DCI) to a UE, e.g. UE1 110, to schedule a transportblock (TB) to be transmitted from the BS 101 to the UE1 110. The DCI mayinclude a plurality of transmission parameters related to the transportblocks to be transmitted. Based on the plurality of transmissionparameters, the UE may determine a transport block size (TBS) fortransmission of the transport blocks. According to various embodiments,the TBS determination may be performed by the BS and/or the UE, and maybe applied to downlink and/or uplink TB transmissions.

Below is a method for calculating TBS by using an existing formula forTBS determination. The method of calculation is to calculateN_(RE)×ν×Q_(m)×R to achieve an intermediate value TBS_temp of thetransport block bit size. The meanings of these parameters are shown asfollows: ν is the number of layers of transportation; Q_(m) is themodulation order, which can be obtained from the MCS index; R is thecode rate, which can be obtained according to the index of MCS; N_(RE)is the number of resource elements (REs) whose value is Y×N^(XL) _(PRB),where N^(XL) _(PRB) is the number of PRBs allocated, Y is the quantizedvalue of X that is the number of REs per PRB, X=12×N^(XL)_(symb)−X_(d)−X_(oh), and X_(d) is the number of REs occupied by ademodulation reference signal (DMRS) in each PRB in the allocatedduration, X_(oh) is a total overhead occupied by a channel statusindicator-reference signal (CSI-RS) and CORESET information, which issemi-statically determined, where the occupancy of the uplink anddownlink may not be the same. After the intermediate value TBS_temp isobtained, the actual TBS is determined according to the channel coding.It has been determined that the TBS must meet the requirements including(a) the multiple of 8 and (b) the code block size (CBS) is equal foreach code block after segmentation. The specific calculation methodincludes: based on the code block segmentation requirements, firstdetermine the number of blocks C via the intermediate value, and thenfind the least common multiple of 8 and C, i.e. LCM (8, C), to quantifythe TBS, that is: TBS=function(TBS_temp/δ)×δ, wherein, function(•) meansrounding, rounding up, rounding down, or keeping the original value; δis the quantization step size of TBS, its value is the least commonmultiple of 8 and code block number C, i.e. δ=LCM(8, C).

Based on the above mentioned method of determining the TBS, when thenumber of PRBs is small and the modulation order is low, the calculatedTBS is small and may deviate from the actual transmitted TBS, resultingin a very unstable link. For example, when the number of allocated REsis 132, the number of PRBs is 1, and the number of layers is 1, asimulated link stability of the MCS table with a downlink 64-QuadratureAmplitude Modulation (64 QAM) is shown in the plot 140 of FIG. 1B. FIG.1B utilizes deltaSNR (i.e. ΔSNR) to represent link stability with theTBS calculated using this method to achieve a target BLER=10%. As shownin FIG. 1B, when the MCS index is low, the deltaSNR fluctuates between0.4 and 1.7, instead of stabilizing around 1.

FIG. 1C illustrates an exemplary simulation result 150 ofsignal-to-noise ratio (SNR) performance change vs. MCS index, based onthe above mentioned method. As shown in FIG. 1C, when the MCS index islow (e.g. between 0 and 10), the SNR curve is not so smooth as the SNRcurve when the MCS index is high (e.g. between 20 and 28). As shown inFIG. 1C, given an MCS index range (e.g. between 0 and 10), the SNR curvecorresponding to a lower PRB=1 is not so smooth as the SNR curvecorresponding to a higher PRB=6, where a smoother SNR curve indicates amore stable link.

Table 1D below shows the TBS values calculated based on the abovementioned method, with the allocated resource N_(RE) ^(PRB)=132.

TABLE 1D MCS PRB Index Q_(m) 1 2 3 4 5 6 0 2 16 48 80 112 144 176 1 2 3272 112 152 192 232 2 2 40 88 136 184 240 288 3 2 56 120 184 248 312 3764 2 64 144 224 304 384 464 5 2 88 184 280 376 472 576 6 2 104 216 336448 568 680 7 2 120 256 392 528 664 800 8 2 144 296 456 608 768 920 9 2160 336 512 688 864 1040 10 4 160 336 512 688 864 1040 11 4 184 376 576768 960 1160 12 4 208 432 656 880 1104 1328 13 4 240 496 744 1000 12481504 14 4 272 560 840 1128 1416 1696 15 4 304 624 944 1256 1576 1896 164 328 664 1008 1344 1680 2024 17 6 328 664 1008 1344 1680 2024 18 6 352712 1072 1432 1792 2152 19 6 384 784 1184 1584 1984 2384 20 6 424 8641304 1744 2184 2616 21 6 464 944 1416 1896 2376 2848 22 6 504 1016 15362048 2560 3080 23 6 544 1104 1656 2216 2768 3328 24 6 584 1184 1776 23762976 3568 25 6 624 1264 1896 2536 3168 3808 26 6 664 1336 2016 2688 33684032 27 6 696 1400 2104 2808 3512 4208 28 6 720 1456 2184 2920 3656 4376

Table 1E below shows the simulated values of ΔSNR of adjacent MCSs, withthe TBS values calculated based on the above mentioned method, theallocated resource N_(RE) ^(PRB)=132, and a target BLER=10%.

TABLE 1E ΔSNR PRB I_(MCS) 1 2 3 4 5 6 0 NaN NaN NaN NaN NaN NaN 1 1.64781.3574 1.2757 1.0864 1.0946 1.039 2 0.6008 0.6385 0.6852 0.7897 0.8810.9065 3 1.2157 1.2039 1.2463 1.225 1.1019 1.1653 4 0.4161 0.792 0.90850.9571 0.9905 1.0053 5 1.2762 1.1092 1.008 1.0476 1.0161 1.0851 6 0.89670.8945 1.0217 0.9632 1.0167 0.9328 7 0.6697 0.9073 0.8472 0.9098 0.9260.9555 8 1.104 0.9149 0.9392 0.9579 0.9554 0.9353 9 0.6058 0.8287 0.87870.8711 0.8573 0.9051 10 NaN NaN NaN NaN NaN NaN 11 0.7741 0.709 0.70910.7192 0.6592 0.701 12 0.7335 0.8537 0.8488 0.8222 0.8916 0.8522 130.9696 0.9846 0.8929 0.9243 0.9018 0.91 14 1.0189 0.9393 0.9285 0.9780.9589 0.9497 15 0.9166 0.9384 1.0292 0.9518 1.0096 1.0164 16 0.6910.6064 0.6579 0.6382 0.606 0.6531 17 NaN NaN NaN NaN NaN NaN 18 0.58710.6526 0.5133 0.5929 0.6074 0.5472 19 0.8761 0.8589 0.9683 0.9294 0.95980.9798 20 0.9768 1.0166 1.0144 1.0278 1.0026 0.9999 21 0.9947 0.9920.9195 0.9368 0.9457 0.9483 22 0.962 0.8876 1.0037 0.9546 0.9617 0.987923 0.9928 1.1357 1.0201 1.0584 0.9959 0.9943 24 0.9511 0.9426 0.95960.9489 1.0049 0.9808 25 1.0099 1.0097 0.9852 1.0005 0.9711 1.0125 261.061 0.9384 1.0496 1.0067 1.0731 1.026 27 1.0414 1.0513 0.9398 0.98660.9268 0.9365 28 0.9567 1.0495 1.031 1.0579 1.0838 1.0464

In response to the link stability problem of the above mentioned method,the present disclosure provides a novel TBS calculation method toimprove the above calculation formula of TBS, by introducing acorrection factor, and determine the functional relationship between therelevant parameters, to ensure a stable link without losing flexibility.

In one embodiment, the novel TBS calculation method is designed byadding a correction factor β. The correction factor is a function of PRBnumber and/or MCS order and/or spectral efficiency (or code rate). Fordifferent PRB numbers and/or different MCS orders and/or differentspectral efficiencies (or code rates), the value of β may be different.

In another embodiment, the novel TBS calculation method is designed bymodifying the total number of REs. N_(RE) is a function of PRB numberand/or MCS order. For different PRB numbers and/or different MCS orders,the number of REs can be quantified differently.

In yet another embodiment, the novel TBS calculation method is designedby modifying the code rate or spectral efficiency. Each of them is afunction of PRB number and/or MCS order. For different PRB numbersand/or different MCS orders, the value of code rate or spectralefficiency may be different.

The present disclosure provides a novel design of a set of available TBSvalues, by developing a fixed quantization step size for TBS in eachgiven TBS range. Different quantization steps for TBS may be designed indifferent ranges; and the quantization step size increases when TBSincreases. This can both ensure same TBS during initial transmission andretransmission, and ensure that the granularity of available TBS is nottoo low. The quantization step may also be a function of the number ofPRBs and/or MCS orders and/or spectral efficiency and/or code rate.

FIG. 2 illustrates a block diagram of a user equipment (UE) 200, inaccordance with some embodiments of the present disclosure. The UE 200is an example of a device that can be configured to implement thevarious methods described herein. As shown in FIG. 2, the UE 200includes a housing 240 containing a system clock 202, a processor 204, amemory 206, a transceiver 210 comprising a transmitter 212 and receiver214, a power module 208, a control information analyzer 220, anintermediate transport block size calculator 222, a transport block sizemodifier 224, and a final transport block size determiner 226.

In this embodiment, the system clock 202 provides the timing signals tothe processor 204 for controlling the timing of all operations of the UE200. The processor 204 controls the general operation of the UE 200 andcan include one or more processing circuits or modules such as a centralprocessing unit (CPU) and/or any combination of general-purposemicroprocessors, microcontrollers, digital signal processors (DSPs),field programmable gate array (FPGAs), programmable logic devices(PLDs), controllers, state machines, gated logic, discrete hardwarecomponents, dedicated hardware finite state machines, or any othersuitable circuits, devices and/or structures that can performcalculations or other manipulations of data.

The memory 206, which can include both read-only memory (ROM) and randomaccess memory (RAM), can provide instructions and data to the processor204. A portion of the memory 206 can also include non-volatile randomaccess memory (NVRAM). The processor 204 typically performs logical andarithmetic operations based on program instructions stored within thememory 206. The instructions (a.k.a., software) stored in the memory 206can be executed by the processor 204 to perform the methods describedherein. The processor 204 and memory 206 together form a processingsystem that stores and executes software. As used herein, “software”means any type of instructions, whether referred to as software,firmware, middleware, microcode, etc. which can configure a machine ordevice to perform one or more desired functions or processes.Instructions can include code (e.g., in source code format, binary codeformat, executable code format, or any other suitable format of code).The instructions, when executed by the one or more processors, cause theprocessing system to perform the various functions described herein.

The transceiver 210, which includes the transmitter 212 and receiver214, allows the UE 200 to transmit and receive data to and from a remotedevice (e.g., the BS or another UE). An antenna 250 is typicallyattached to the housing 240 and electrically coupled to the transceiver210. In various embodiments, the UE 200 includes (not shown) multipletransmitters, multiple receivers, and multiple transceivers. In oneembodiment, the antenna 250 is replaced with a multi-antenna array 250that can form a plurality of beams each of which points in a distinctdirection. The transmitter 212 can be configured to wirelessly transmitpackets having different packet types or functions, such packets beinggenerated by the processor 204. Similarly, the receiver 214 isconfigured to receive packets having different packet types orfunctions, and the processor 204 is configured to process packets of aplurality of different packet types. For example, the processor 204 canbe configured to determine the type of packet and to process the packetand/or fields of the packet accordingly.

In a wireless communication, the UE 200 may receive control informationfrom a BS. The control information may be downlink control information(DCI) in this embodiment. For example, the control information analyzer220 may receive, via the receiver 214, DCI including a plurality oftransmission parameters related to transport blocks to be transmittedbetween the UE 200 and the BS, e.g. from the BS to the UE 200. Thecontrol information analyzer 220 may analyze the DCI to identify theplurality of transmission parameters, which may include at least one of:a quantity of layers configured for transmission of the transportblocks; a modulation order configured for transmission of the transportblocks; a code rate configured for transmission of the transport blocks;a quantity of physical resource blocks configured for transmission ofthe transport blocks; a quantity of resource elements per each physicalresource block; a total quantity of resource elements for transmissionof the transport blocks, which is a product of the quantity of physicalresource blocks and the quantity of resource elements per physicalresource block; and a spectral efficiency configured for transmission ofthe transport blocks, which is equal to a product of the modulationorder and the code rate. The control information analyzer 220 may sendthe analyzed DCI including the plurality of transmission parameters tothe intermediate transport block size calculator 222 for calculating anintermediate transport block size (TBS), and to the transport block sizemodifier 224 for modifying the intermediate TBS to generate a modifiedTBS.

The intermediate transport block size calculator 222 in this examplereceives the analyzed DCI including the plurality of transmissionparameters from the control information analyzer 220. Based on theplurality of transmission parameters, the intermediate transport blocksize calculator 222 calculates an intermediate TBS for the transportblocks to be transmitted from the BS to the UE 200. In one embodiment,the intermediate transport block size calculator 222 can calculate theintermediate TBS based on the above mentioned method corresponding toFIG. 1B and FIG. 1C. The intermediate transport block size calculator222 transmits the intermediate TBS to the transport block size modifier224 for modifying the intermediate TBS to generate a modified TBS.

The transport block size modifier 224 in this example can receive theplurality of transmission parameters from the control informationanalyzer 220 and receive the intermediate TBS from the intermediatetransport block size calculator 222. The transport block size modifier224 first determines whether a condition is met based on at least one ofthe plurality of transmission parameters and at least one threshold. Inone embodiment, the condition is met when at least one of the followinghappens: the quantity of physical resource blocks is smaller than orequal to a first threshold, e.g. 2; the modulation order is smaller thanor equal to a second threshold, e.g. 4; the total quantity of resourceelements is smaller than a third threshold; and the intermediatetransport block size is smaller than a fourth threshold, e.g. 4000.

When the condition is met, the transport block size modifier 224modifies the intermediate transport block size to generate a modifiedtransport block size. In one embodiment, when the condition is met, thetransport block size modifier 224 determines a correction factor basedon at least one of: the quantity of physical resource blocks, and themodulation order and the spectral efficiency, and multiplies theintermediate transport block size by the correction factor to generatethe modified transport block size.

In another embodiment, when the condition is met, the transport blocksize modifier 224 determines a modified quantity of resource elementsbased on the total quantity of resource elements and a set of resourceelement quantities after quantization, and replaces the total quantityof resource elements with the modified quantity of resource elements inthe calculation of the intermediate transport block size to generate themodified transport block size.

In yet another embodiment, when the condition is met, the transportblock size modifier 224 determines a modified code rate based on atleast one of: the quantity of physical resource blocks and themodulation order and the spectral efficiency, and replaces the code ratewith the modified code rate in the calculation of the intermediatetransport block size to generate the modified transport block size.

In a different embodiment, the modified transport block size includesbits for cyclic redundancy check (CRC) of each of the transport blocks.Transmission of the transport blocks based on a calculated transportblock size leads to a better link stability when the calculatedtransport block size is the modified transport block size than that whenthe calculated transport block size is the intermediate transport blocksize. The link stability may be determined based on a change of asignal-to-noise ratio required to achieve a target block error rate fortransmission of the transport blocks, given a discrepancy between thecalculated transport block size and an actual transport block size usedfor the transmission. The transport block size modifier 224 transmitsthe modified TBS to the final transport block size determiner 226 fordetermining a final TBS for transmission of the transport blocks.

The final transport block size determiner 226 in this example mayreceive the plurality of transmission parameters from the controlinformation analyzer 220, and receive the modified TBS from thetransport block size modifier 224. The final transport block sizedeterminer 226 can determine a final transport block size based on themodified transport block size for transmission of the transport blocks.

In one embodiment, the final transport block size determiner 226generates a quantized set of transport block sizes, where a quantizationstep, from a transport block to next transport block in the quantizedset, is a function of at least one of the following transmissionparameters: the quantity of physical resource blocks, the modulationorder and the spectral efficiency. The final transport block sizedeterminer 226 then determines the final transport block size based on atransport block size that is closest to the modified transport blocksize, among transport block sizes that are in the quantized set and notsmaller than the modified transport block size.

In another embodiment, the final transport block size determiner 226rounds up the modified transport block size to a closest larger integerto generate an integer transport block size; determines a quantity ofcode blocks in each of the transport blocks based on the integertransport block size and a block segmentation rule related to channelcoding; and calculates the final transport block size based on theinteger transport block size and the quantity of code blocks to ensurethe multiple of 8 and equal code block size after block segmentation ofthe transport blocks. For example, the final transport block sizedeterminer 226 can determine a least common multiple of eight and thequantity of code blocks; and determine the final transport block sizebased on an integer that is closest to the integer transport block size,among integers that are divisible by the least common multiple and notsmaller than the integer transport block size. Because one byte includeseight bits, being divisible by the least common multiple of eight andthe quantity of code blocks ensures both the multiple of 8 and equalcode block size after block segmentation of the transport blocks.

In the present disclosure, the expressions “X is divisible by Y” and “Xis evenly divisible by Y” can be used interchangeably to mean that X isa (positive integer) multiple of Y and there is no remainder.

In yet another embodiment, the final transport block size determiner 226generates a quantized set of transport block sizes, where thequantization step, from a transport block to next transport block in thequantized set, increases as the transport block size increases. Thefinal transport block size determiner 226 then determines the finaltransport block size based on a transport block size that is closest tothe modified transport block size, among transport block sizes that arein the quantized set and not smaller than the modified transport blocksize.

In still another embodiment, the final transport block size determiner226 generates a quantized set of transport block sizes, where thequantization step, from a transport block to next transport block in thequantized set, is determined to ensure granularity of the quantized setis larger than a threshold; and determines the final transport blocksize based on a transport block size that is closest to the modifiedtransport block size, among transport block sizes that are in thequantized set and not smaller than the modified transport block size. Inthis embodiment, the quantization step is determined to ensure that thefinal transport block size is the same for both an initial transmissionand a re-transmission of a transport block.

The power module 208 can include a power source such as one or morebatteries, and a power regulator, to provide regulated power to each ofthe above-described modules in FIG. 2. In some embodiments, if the UE200 is coupled to a dedicated external power source (e.g., a wallelectrical outlet), the power module 208 can include a transformer and apower regulator.

The various modules discussed above are coupled together by a bus system230. The bus system 230 can include a data bus and, for example, a powerbus, a control signal bus, and/or a status signal bus in addition to thedata bus. It is understood that the modules of the UE 200 can beoperatively coupled to one another using any suitable techniques andmediums.

Although a number of separate modules or components are illustrated inFIG. 2, persons of ordinary skill in the art will understand that one ormore of the modules can be combined or commonly implemented. Forexample, the processor 204 can implement not only the functionalitydescribed above with respect to the processor 204, but also implementthe functionality described above with respect to the intermediatetransport block size calculator 222. Conversely, each of the modulesillustrated in FIG. 2 can be implemented using a plurality of separatecomponents or elements.

FIG. 3 illustrates a flow chart for a method 300 performed by a UE, e.g.the UE 200 in FIG. 2, for determining a transport block size in awireless communication, in accordance with some embodiments of thepresent disclosure. At operation 302, the UE receives, from a BS,control information including transmission parameters related totransport blocks to be transmitted between the UE and the BS. Atoperation 304, the UE calculates an intermediate transport block sizefor the transport blocks based on the transmission parameters. The UEmodifies at operation 306 the intermediate transport block size togenerate a modified transport block size in response to at least oneevent. At operation 308, the UE determines a final transport block sizebased on a transport block size that is closest to the modifiedtransport block size among transport block sizes that are in a quantizedset and not smaller than the modified transport block size.

FIG. 4 illustrates a block diagram of a BS 400, in accordance with someembodiments of the present disclosure. The BS 400 is an example of adevice that can be configured to implement the various methods describedherein. As shown in FIG. 4, the BS 400 includes a housing 440 containinga system clock 402, a processor 404, a memory 406, a transceiver 410comprising a transmitter 412 and a receiver 414, a power module 408, acontrol information generator 420, an intermediate transport block sizecalculator 422, a transport block size modifier 424, and a finaltransport block size determiner 426.

In this embodiment, the system clock 402, the processor 404, the memory406, the transceiver 410 and the power module 408 work similarly to thesystem clock 202, the processor 204, the memory 206, the transceiver 210and the power module 208 in the UE 200. An antenna 450 or amulti-antenna array 450 is typically attached to the housing 440 andelectrically coupled to the transceiver 410.

The control information generator 420 may generate a plurality oftransmission parameters related to transport blocks to be transmittedbetween the BS 400 and a UE, e.g. from the BS 400 to the UE 200. Theplurality of transmission parameters may include at least one of: aquantity of layers configured for transmission of the transport blocks;a modulation order configured for transmission of the transport blocks;a code rate configured for transmission of the transport blocks; aquantity of physical resource blocks configured for transmission of thetransport blocks; a quantity of resource elements per each physicalresource block; a total quantity of resource elements for transmissionof the transport blocks, which is a product of the quantity of physicalresource blocks and the quantity of resource elements per physicalresource block; and a spectral efficiency configured for transmission ofthe transport blocks, which is equal to a product of the modulationorder and the code rate. The control information generator 420 may sendthe generated transmission parameters to the intermediate transportblock size calculator 422 for calculating an intermediate transportblock size (TBS), and to the transport block size modifier 424 formodifying the intermediate TBS to generate a modified TBS. The controlinformation generator 420 also generates and transmits, via thetransmitter 412, control information that includes the plurality oftransmission parameters and a transport block size, e.g. a finaltransport block size as discussed later, to the UE.

In one embodiment, the control information is downlink controlinformation (DCI). In one example, the final transport block size isdetermined by the BS 400, such that the BS informs the UE 200 about thefinal transport block size via the DCI. In another example, the finaltransport block size is determined by the UE 200, such that the DCItransmitted by the BS 400 does not include the final transport blocksize. In yet another example, the final transport block size isdetermined by both the BS 400 and the UE 200 according to the same rule,such that the DCI transmitted by the BS 400 does not include the finaltransport block size.

The intermediate transport block size calculator 422 in this examplereceives the plurality of transmission parameters from the controlinformation generator 420. Based on the plurality of transmissionparameters, the intermediate transport block size calculator 422calculates an intermediate TBS for the transport blocks to betransmitted from the BS 400 to the UE 200. In one embodiment, theintermediate transport block size calculator 422 can calculate theintermediate TBS based on the above mentioned method corresponding toFIG. 1B and FIG. 1C. The intermediate transport block size calculator422 transmits the intermediate TBS to the transport block size modifier424 for modifying the intermediate TBS to generate a modified TBS.

The transport block size modifier 424 in this example can receive theplurality of transmission parameters from the control informationgenerator 420 and receive the intermediate TBS from the intermediatetransport block size calculator 422. The transport block size modifier424 first determines whether a condition is met based on at least one ofthe plurality of transmission parameters and at least one threshold. Inone embodiment, the condition is met when at least one of the followinghappens: the quantity of physical resource blocks is smaller than orequal to a first threshold, e.g. 2; the modulation order is smaller thanor equal to a second threshold, e.g. 4; the total quantity of resourceelements is smaller than a third threshold; and the intermediatetransport block size is smaller than a fourth threshold, e.g. 4000.

When the condition is met, the transport block size modifier 424modifies the intermediate transport block size to generate a modifiedtransport block size. In one embodiment, when the condition is met, thetransport block size modifier 424 determines a correction factor basedon at least one of: the quantity of physical resource blocks, and themodulation order and the spectral efficiency, and multiplies theintermediate transport block size by the correction factor to generatethe modified transport block size.

In another embodiment, when the condition is met, the transport blocksize modifier 424 determines a modified quantity of resource elementsbased on the total quantity of resource elements and a set of resourceelement quantities after quantization, and replaces the total quantityof resource elements with the modified quantity of resource elements inthe calculation of the intermediate transport block size to generate themodified transport block size.

In yet another embodiment, when the condition is met, the transportblock size modifier 424 determines a modified code rate based on atleast one of: the quantity of physical resource blocks and themodulation order and the spectral efficiency, and replaces the code ratewith the modified code rate in the calculation of the intermediatetransport block size to generate the modified transport block size.

In a different embodiment, the modified transport block size includesbits for CRC of each of the transport blocks. Transmission of thetransport blocks based on a calculated transport block size leads to abetter link stability when the calculated transport block size is themodified transport block size than that when the calculated transportblock size is the intermediate transport block size. The link stabilitymay be determined based on a change of a signal-to-noise ratio requiredto achieve a target block error rate for transmission of the transportblocks, given a discrepancy between the calculated transport block sizeand an actual transport block size used for the transmission. Thetransport block size modifier 424 sends the modified TBS to the finaltransport block size determiner 426 for determining a final TBS fortransmission of the transport blocks.

The final transport block size determiner 426 in this example mayreceive the plurality of transmission parameters from the controlinformation generator 420, and receive the modified TBS from thetransport block size modifier 424. The final transport block sizedeterminer 426 can determine a final transport block size based on themodified transport block size for transmission of the transport blocks.

In one embodiment, the final transport block size determiner 426generates a quantized set of transport block sizes, where a quantizationstep, from a transport block to next transport block in the quantizedset, is a function of at least one of the following transmissionparameters: the quantity of physical resource blocks, the modulationorder and the spectral efficiency. The final transport block sizedeterminer 426 then determines the final transport block size based on atransport block size that is closest to the modified transport blocksize, among transport block sizes that are in the quantized set and notsmaller than the modified transport block size.

In another embodiment, the final transport block size determiner 426rounds up the modified transport block size to a closest larger integerto generate an integer transport block size; determines a quantity ofcode blocks in each of the transport blocks based on the integertransport block size and a block segmentation rule related to channelcoding; and calculates the final transport block size based on theinteger transport block size and the quantity of code blocks to ensurethe multiple of 8 and equal code block size after block segmentation ofthe transport blocks. For example, the final transport block sizedeterminer 426 can determine a least common multiple of eight and thequantity of code blocks; and determine the final transport block sizebased on an integer that is closest to the integer transport block size,among integers that are divisible by the least common multiple and notsmaller than the integer transport block size. Because one byte includeseight bits, being divisible by the least common multiple of eight andthe quantity of code blocks ensures both the multiple of 8 and equalcode block size after block segmentation of the transport blocks.

In yet another embodiment, the final transport block size determiner 426generates a quantized set of transport block sizes, where thequantization step, from a transport block to next transport block in thequantized set, increases as the transport block size increases. Thefinal transport block size determiner 426 then determines the finaltransport block size based on a transport block size that is closest tothe modified transport block size, among transport block sizes that arein the quantized set and not smaller than the modified transport blocksize.

In still another embodiment, the final transport block size determiner426 generates a quantized set of transport block sizes, where thequantization step, from a transport block to next transport block in thequantized set, is determined to ensure granularity of the quantized setis larger than a threshold; and determines the final transport blocksize based on a transport block size that is closest to the modifiedtransport block size, among transport block sizes that are in thequantized set and not smaller than the modified transport block size. Inthis embodiment, the quantization step is determined to ensure that thefinal transport block size is the same for both an initial transmissionand a re-transmission of a transport block.

The various modules discussed above are coupled together by a bus system430. The bus system 430 can include a data bus and, for example, a powerbus, a control signal bus, and/or a status signal bus in addition to thedata bus. It is understood that the modules of the BS 400 can beoperatively coupled to one another using any suitable techniques andmediums.

Although a number of separate modules or components are illustrated inFIG. 4, persons of ordinary skill in the art will understand that one ormore of the modules can be combined or commonly implemented. Forexample, the processor 404 can implement not only the functionalitydescribed above with respect to the processor 404, but also implementthe functionality described above with respect to the intermediatetransport block size calculator 422. Conversely, each of the modulesillustrated in FIG. 4 can be implemented using a plurality of separatecomponents or elements.

FIG. 5 illustrates a flow chart for a method 500 performed by a BS, e.g.the BS 400 in FIG. 4, for determining a transport block size in awireless communication, in accordance with some embodiments of thepresent disclosure. At operation 502, the BS generates a plurality oftransmission parameters related to transport blocks. At operation 504,the BS transmits control information that comprises the plurality oftransmission parameters to a UE. At operation 506, the BS calculates anintermediate transport block size for the transport blocks based on theplurality of transmission parameters. The BS modifies at operation 508the intermediate transport block size to generate a modified transportblock size in response to an event that the intermediate TBS is smallerthan a threshold. The BS determines at operation 510 a final transportblock size based on a transport block size that is closest to themodified transport block size among transport block sizes that are in aquantized set and not smaller than the modified transport block size. Atoperation 512, the BS communicates with the UE using the transportblocks based on the final transport block size.

In one embodiment, the roles of the BS 400 and the UE 200 in FIGS. 2-5are exchanged, where the UE 200 generates and transmits uplink controlinformation to the BS 400. The TBS is calculated and determined fortransport blocks to be transmitted from the UE 200 to the BS 400 foruplink transmissions, in a similar manner to the manner discussed abovefor downlink transmissions.

Different embodiments of the present disclosure will now be described indetail hereinafter. It is noted that the features of the embodiments andexamples in the present disclosure may be combined with each other inany manner without conflict.

According to various embodiments of the present disclosure, a TBScalculation method is provided and can be applied to a new radio (NR)access technology communication system. The method proposed in thepresent disclosure may be applied to a fifth generation (5G) mobilecommunication system or other wireless or wired communication system.The data transmission direction is that a base station sends data(downlink transmission service data) to a mobile user or a mobile usersends data (uplink transmission service data) to the base station.Mobile users include: mobile devices, access terminals, user terminals,subscriber stations, subscriber units, mobile stations, remote stations,remote terminals, user agents, user equipment, user devices, or someother terminology. The base station includes: an access point (AP), anode B, a radio network controller (RNC), an evolved Node B (eNB), abase station controller (BSC), Base Transceiver Station (BTS), a BaseStation (BS), a Transceiver Function (TF), a radio router, a radiotransceiver, a basic service unit, an extension service unit, a RadioBase Station (RBS), or some other terminology. A TBS calculation methodprovided in the present disclosure may be applied to an enhanced MobileBroadband (eMBB) scenario, an ultra-reliable low-latency communications(URLLC) scenario or a massive Machine Type Communications (mMTC)scenario, in the NR access technology.

In a first embodiment, the functional model for TBS calculation is:TBS=F(β), with a specific form shown as follows:

${TBS} = {{{function}\left( \frac{{function}\left( {\beta \times {{function}\left( {Q_{m} \times R \times v \times Y \times N_{PRB}^{XL}} \right)}} \right)}{\delta} \right)} \times {\delta.}}$

In the above formula, the correction factor β is a function of (a) thenumber of PRBs allocated for uplink or downlink, and/or (b) the order ofthe modulation and coding Q_(m), and/or (c) the code rate R (or spectrumefficiency); function(•) indicates rounding, rounding up, rounding down,or retaining the original value; Y is the quantized value of X that isthe number of REs per PRB; δ is the quantization step of the TBS. Sincethe correction factor is mainly added to improve the link stability whenthe PRB is small and when the order of the MCS is low, the value of βcan be determined by Q_(m) and N^(XL) _(PRB).

In a first situation, when the PRB is small and/or the MCS order is low,the correction factor is set to be a fraction close to 1, e.g. 0.9. Forthe sake of simple hardware implementation, the value of the correctionfactor can be taken as

$\frac{2^{n\; 1} - 1}{2^{n\; 1}}.$

In a second situation, when the MCS order is high and the allocatedspectrum efficiency (SE) is the same as the SE at the modulation orderhopping (where the modulation order changes from an MCS index to anadjacent MCS index in the MCS table) in the MCS table, the correctionfactor is also set to be a fraction close to 1, e.g. 0.94. For the sakeof simple hardware implementation, the value of the correction factorcan be taken as

$\frac{2^{n\; 2} - 1}{2^{n\; 2}}.$

In general, the correction factor in the second situation is larger thanthat in the first situation. When the RE value in each PRB changes, thecorrespondingly obtained link stability will also change. Therefore, thevalues of the correction factors may be different for different REvalues. For example, when the RE value in each PRB is 120, thecorrection factor can be set to be 1.

When the PRB is larger and/or the order of the MCS is higher, the valueof the correction factor is set to be 1. Because when the PRB is largerand the MCS is higher, the TBS is larger, and the interval of actuallyavailable TBSs is also larger. Therefore, the calculated TBS does notneed to be modified to obtain good link stability.

According to one example, the value of the correction factor β is shownin the following table:

Q_(m) S_(higherMCS) β S_(higherMCS) at not at SE N_(PRB) S_(lowerMCS) SEoverlap overlap ≤ x $\beta = \frac{31}{32}$ β = 63/64 β = 1 > x β = 1

The functional model of the correction factor β is shown below:

$\beta = \left\{ {\begin{matrix}{\frac{2^{n\; 1} - 1}{2^{n\; 1}},{n\; 1}} & {{N_{PRB}^{XL} < x},{{({or})Q_{m}} \in S_{{lower}\; \_ \; {MCS}}}} \\{\frac{2^{n\; 2} - 1}{2^{n\; 2}},{n\; 2}} & {Q_{m} \in S_{{overlappingSE}\mspace{11mu} \_ \; {higherMCS}}} \\1 & {{else}.}\end{matrix}.} \right.$

In the above, x indicates the number of PRBs, for example, x=6;S_(lowerMCS) represents a set of Q_(m) values in lower-order modulation;S_(higherMCS) represents a set of Q_(m) values in higher-ordermodulation, S_(overlappingSE_high_higherMCS) represents a larger Q_(m)value of two different modulation orders at SE overlap (where the SEvalue does not change from an MCS index to an adjacent MCS index in theMCS table) in higher-order modulation. When the number of PRBs is smalland the order of MCS is low, the value β=(2^(n)−1)/2^(n) can not onlyachieve better performance but also be easy to implement by hardware.For example, when the value of n1 is 5, β=31/32; when the value of n2 is6, β=63/64. In the process of hardware implementation, one just needs totruncate the TBS or intermediate TBS (referred to as TBS_temp) andperform a subtraction to complete a corresponding multiplication of β.

The steps to determine TBS in this embodiment include the following:

Step 1, according to the obtained transmission parameters Q_(m), R, ν, Yand N^(XL) _(PRB), determine the value of β based on the number of PRBsand the MCS order.

Step 2, calculate the TBS intermediate value TBS_temp, which can bedivided into two cases.

In case 1: First, the formula Q_(m)×R×ν×Y×N^(XL) _(PRB) is used tocalculate and round up to obtain TBS_temp. The TBS_temp is divided intoblocks according to the code block segmentation rule of the channelcoding. Note that TBS_temp includes the transport block CRC check bits(TB_CRC). Second, correct TBS_temp by multiplying it with the correctionfactor β. Finally, assuming that the number of code blocks that need tobe transmitted is C, in order to obtain the TBS with the multiple of 8and equal CBS, it is required that TBS_temp can be divisible by the LCM(8, C) which is the least common multiple of 8 and C. The formula forthis process is shown below:

${TBS} = {{{ceil}\left( {\beta \times \frac{TBS\_ temp}{{LCM}\left( {8,C} \right)}} \right)} \times {{{LCM}\left( {8,C} \right)}.}}$

In case 2: formula β×Q_(m)×R×ν×Y×N^(XL) _(PRB) is used to calculate themodified TBS_temp. The TBS_temp is divided into blocks according to thecode block segmentation rule of the channel coding. Note that TBS_tempincludes the transport block CRC check bits (TB_CRC). Assuming that thenumber of code blocks that need to be transmitted is C, in order toobtain the TBS with the multiple of 8 and equal CBS, it is required thatTBS temp can be divisible by the LCM (8, C) which is the least commonmultiple of 8 and C. The formula for this process is shown below:

${TBS} = {{{ceil}\left( \frac{\beta \times Q_{m} \times R \times v \times Y \times N_{PRB}^{XL}}{{LCM}\left( {8,C} \right)} \right)} \times {{{LCM}\left( {8,C} \right)}.}}$

FIG. 6A illustrates an exemplary simulation result 610 of link stabilitychanges vs. MCS index, in accordance with this embodiment. FIG. 6Autilizes deltaSNR (i.e. ΔSNR) to represent link stability with the TBScalculated and modified using the method in this embodiment to achieve atarget BLER=10%. As shown in FIG. 6A, when the MCS index is low (e.g.between 0 and 10), the deltaSNR fluctuates between 0.6 and 1.2, lessthan the fluctuation in the same MCS range shown in FIG. 1B.

FIG. 6B illustrates an exemplary simulation result 620 of SNRperformance change vs. MCS index, in accordance with this embodiment. Asshown in FIG. 6B, when the MCS index is low (e.g. between 0 and 10), theSNR curve is not so smooth as the SNR curve when the MCS index is high(e.g. between 20 and 28). As shown in FIG. 6B, given an MCS index range(e.g. between 0 and 10), the SNR curve corresponding to a lower PRB,e.g. when PRB=1, is not so smooth as the SNR curve corresponding to ahigher PRB, e.g. when PRB=6, where a smoother SNR curve indicates a morestable link.

Table 6C below shows the TBS values calculated and corrected with thecorrection factor β based on the above mentioned method in the firstembodiment, with the allocated resource N_(RE) ^(PRB)=132.

TABLE 6C MCS PRB Index Q_(m) 1 2 3 4 5 6 0 2 16 40 72 96 128 152 1 2 2464 96 136 168 208 2 2 32 80 120 168 216 256 3 2 48 104 160 224 280 336 42 64 128 200 272 344 416 5 2 80 168 256 344 432 520 6 2 96 200 304 408512 616 7 2 112 232 352 480 600 720 8 2 128 272 408 552 688 832 9 2 144304 464 624 776 936 10 4 144 304 464 624 776 936 11 4 160 336 512 688864 1040 12 4 192 392 592 800 1000 1200 13 4 216 448 672 904 1128 135214 4 248 504 760 1016 1272 1528 15 4 272 560 848 1136 1424 1704 16 4 304624 944 1264 1576 1896 17 6 304 624 944 1264 1576 1896 18 6 352 712 10721432 1792 2152 19 6 384 784 1184 1584 1984 2384 20 6 424 864 1304 17442184 2616 21 6 464 944 1416 1896 2376 2848 22 6 504 1016 1536 2048 25603080 23 6 544 1104 1656 2216 2768 3328 24 6 584 1184 1776 2376 2976 356825 6 624 1264 1896 2536 3168 3808 26 6 664 1336 2016 2688 3368 4032 27 6696 1400 2104 2808 3512 4208 28 6 720 1456 2184 2920 3656 4376

Table 6D below shows the simulated values of ΔSNR of adjacent MCSs, withthe TBS values calculated and corrected with the correction factor βbased on the above mentioned method in the first embodiment, theallocated resource N_(RE) ^(PRB)=132, and a target BLER=10%.

TABLE 6D ΔSNR PRB I_(MCS) 1 2 3 4 5 6 0 NaN NaN NaN NaN NaN NaN 1 0.8820.9434 0.9743 0.9459 1.1174 1.1051 2 1.3666 1.0525 0.9866 0.9302 0.89290.9062 3 0.5966 0.9564 1.0075 1.1155 1.2236 1.1064 4 1.0352 1.03950.9661 0.9521 0.9512 0.996 5 0.8758 0.8822 1.1017 1.0529 1.0496 1.0664 61.2971 1.1215 0.9428 0.9689 0.9141 0.9764 7 0.6697 0.6795 0.8543 0.85070.946 0.9578 8 0.6752 0.9349 0.9246 0.9338 0.9039 0.8493 9 1.0346 0.85510.7767 0.7691 0.8518 0.8983 10 NaN NaN NaN NaN NaN NaN 11 0.9388 0.8790.9649 0.9198 0.869 0.9092 12 0.7335 0.8537 0.8488 0.8222 0.8916 0.852213 0.9696 0.9846 0.8929 0.9243 0.9018 0.91 14 1.0189 0.9393 0.9285 0.9780.9589 0.9497 15 0.9166 0.9384 1.0292 0.9518 1.0096 1.0164 16 1.05350.9027 0.9588 0.9697 0.9185 0.9621 17 NaN NaN NaN NaN NaN NaN 18 0.8130.9208 0.7866 0.8594 0.9083 0.8108 19 0.8761 0.8589 0.9683 0.9294 0.95980.9798 20 0.9768 1.0166 1.0144 1.0278 1.0026 0.9999 21 0.9947 0.9920.9195 0.9368 0.9457 0.9483 22 0.962 0.8876 1.0037 0.9546 0.9617 0.987923 0.9928 1.1357 1.0201 1.0584 0.9959 0.9943 24 0.9511 0.9426 0.95960.9489 1.0049 0.9808 25 1.0099 1.0097 0.9852 1.0005 0.9711 1.0125 261.061 0.9384 1.0496 1.0067 1.0731 1.026 27 1.0414 1.0513 0.9398 0.98660.9268 0.9365 28 0.9567 1.0495 1.031 1.0579 1.0838 1.0464

In a second embodiment, the functional model for TBS calculation is:TBS=F(N_(RE)), with a specific form shown as follows:

${TBS} = {{{function}\left( \frac{{function}\left( {Q_{m} \times R \times v \times N_{RE}} \right)}{\delta} \right)} \times {\delta.}}$

In the above formula, N_(RE) represents the number of REs allocated,i.e. N_(RE)=Y×N^(XL) _(PRB); the value of N_(RE) is a function of theorder of the modulation and coding Q_(m); function(•) indicatesrounding, rounding up, rounding down, or retaining the original value; Yis the quantized value of X that is the number of REs per PRB; δ is thequantization step of the TBS. The modification on N_(RE) is to improvethe link stability when the number of total REs is small and the orderof the MCS is low. The modified value of N_(RE) is taken as follows.

In a first situation, when the total number of REs is small and the MCSmodulation order is low, the total number of REs is set to be theminimum value or any other value of the RE set after quantization. Forexample, the RE set after quantization is S_(Y)={120, 126, 132 . . . },then 120 is taken as the total number of REs calculated by TBS. In asecond situation, when the total number of REs is high or the MCSmodulation order is high, the total number of REs is set to be the totalnumber of REs calculated by the allocated parameters, that is,N_(RE)=Y×N^(XL) _(PRB).

According to one example, the total number of REs is set in thefollowing table:

Q_(m) N_(RE) N_(RE) S_(lower) _(—) _(MCS) S_(higher) _(—) _(MCS) ≤xN_(RE)′(a value in S_(Y)) N_(RE) >x N_(RE) N_(RE)

The functional model of the total number of REs is shown below:

$N_{RE} = \left\{ {\begin{matrix}{\min \left( S_{Y} \right)} & {{N_{RE} \leq x},{Q_{m} \in S_{{lower}\; \_ \; {MCS}}},} \\{Y \times N_{PRB}^{XL}} & {{else}.}\end{matrix}.} \right.$

In the above, the value of x is generally 280; S_(lower_MCS) representsa set of Q_(m) values for a lower-order MCS. For example,S_(lower_MCS)={2, 4}, i.e. the value of Q_(m) may be 2 or 4. S_(Y) is acollection of values for Y, for example S_(Y)={120, 126, 132, Λ}; min(SY) represents the minimum value in the set of values of Y.

The steps to determine TBS in this embodiment include the following:

Step 1, according to the obtained transmission parameters Q_(m), R, ν, Yand N^(XL) _(PRB), determine the value of N_(RE).

Step 2, based on Q_(m)×R×ν×N_(RE), calculate and round up to obtainTBS_temp. The TBS_temp includes the transport block CRC check bits(TB_CRC).

Step 3, the TBS_temp is divided into blocks according to the code blocksegmentation rule of the channel coding. Assuming that the number ofdivided code blocks is C, to ensure that the TBS bytes are aligned andthe sizes of the divided code blocks are equal, the TBS_temp needs to bedivisible by the LCM (8, C). The formula for this process is as follows

${TBS} = {{{function}\left( \frac{TBS\_ temp}{{LCM}\left( {8,C} \right)} \right)} \times {{{LCM}\left( {8,C} \right)}.}}$

FIG. 7A illustrates an exemplary simulation result 710 of link stabilitychanges vs. MCS index, in accordance with this embodiment. FIG. 7Autilizes deltaSNR (i.e. ΔSNR) to represent link stability with the TBScalculated and modified using the method in this embodiment to achieve atarget BLER=10%. As shown in FIG. 7A, when the MCS index is low (e.g.between 0 and 10), the deltaSNR fluctuates between 0.6 and 1.5, lessthan the fluctuation in the same MCS range shown in FIG. 1B.

FIG. 7B illustrates an exemplary simulation result 720 of SNRperformance change vs. MCS index, in accordance with this embodiment. Asshown in FIG. 7B, when the MCS index is low (e.g. between 0 and 10), theSNR curve is not so smooth as the SNR curve when the MCS index is high(e.g. between 20 and 28). As shown in FIG. 7B, given an MCS index range(e.g. between 0 and 10), the SNR curve corresponding to a lower PRB,e.g. when PRB=1, is not so smooth as the SNR curve corresponding to ahigher PRB, e.g. when PRB=6, where a smoother SNR curve indicates a morestable link.

Table 7C below shows the TBS values calculated based on the abovementioned method in the second embodiment, with the new RE valueconstraint N_(RE)=120.

TABLE 7C MCS PRB Index Q_(m) 1 2 3 4 5 6 0 2 16 48 72 104 128 160 1 2 2464 96 136 168 208 2 2 32 80 120 168 216 256 3 2 48 104 168 224 280 344 42 64 136 208 280 352 424 5 2 80 168 256 344 432 520 6 2 96 200 304 408512 616 7 2 112 232 360 480 600 728 8 2 128 272 408 552 696 832 9 2 144304 464 624 784 944 10 4 144 304 464 624 784 944 11 4 168 344 520 696872 1048 12 4 192 392 600 800 1008 1208 13 4 216 448 680 904 1136 136814 4 248 504 768 1024 1288 1544 15 4 280 568 856 1144 1432 1720 16 4 296608 912 1224 1528 1840 17 6 296 608 912 1224 1528 1840 18 6 312 640 9681296 1624 1952 19 6 352 712 1080 1440 1800 2168 20 6 384 784 1184 15841984 2384 21 6 424 856 1288 1720 2152 2592 22 6 456 928 1392 1864 23282800 23 6 496 1000 1504 2008 2512 3024 24 6 528 1072 1616 2160 2704 324825 6 568 1144 1720 2304 2880 3456 26 6 600 1216 1832 2440 3056 3672 27 6632 1272 1912 2552 3192 3824 28 6 656 1320 1984 2656 3320 3976

Table 7D below shows the simulated values of ΔSNR of adjacent MCSs, withthe TBS values calculated based on the above mentioned method in thesecond embodiment, with the new RE value constraint N_(RE) ^(PRB)=120,and a target BLER=10%.

TABLE 7D ΔSNR PRB I_(MCS) 1 2 3 4 5 6 0 NaN NaN NaN NaN NaN NaN 1 0.93950.9991 0.9941 1.0927 1.0634 1.0445 2 0.6133 0.7165 0.8077 0.7349 0.96290.7704 3 1.4353 0.9961 1.425 1.2235 1.114 1.2909 4 0.9522 1.082 0.93371.0087 1.0691 0.9922 5 0.9507 0.9945 0.9161 1.0164 1.0182 1.0252 60.8129 0.9562 0.9854 0.9 0.9077 0.947 7 0.779 0.8148 0.9742 0.937 0.94590.9895 8 0.8754 0.9602 0.729 0.9308 0.9566 0.8835 9 0.6579 0.8066 0.95380.8757 0.8866 0.9261 10 NaN NaN NaN NaN NaN NaN 11 0.8816 0.7628 0.72360.701 0.6642 0.6828 12 0.7783 0.8063 0.9026 0.8606 0.9443 0.8973 130.8709 0.9668 0.8987 0.8787 0.8811 0.9138 14 1.0217 0.8844 0.9758 0.96190.9731 0.9531 15 1.0197 1.0427 0.9511 1.0282 0.9549 0.9805 16 0.54050.656 0.6022 0.6477 0.6221 0.6473 17 NaN NaN NaN NaN NaN NaN 18 0.4340.4394 0.5284 0.4999 0.5586 0.5556 19 1.0579 0.9871 1.0226 1.0412 0.97971.0054 20 0.8967 0.9857 0.9636 0.96 1.0236 1.0035 21 1.1022 0.99630.9381 0.9424 0.9095 0.9463 22 0.837 0.9637 0.9214 0.9688 0.943 0.951523 1.0724 1.0106 1.0391 1.014 1.0355 1.0252 24 0.8719 0.9567 0.98950.9685 1.0087 0.9627 25 1.0593 0.9947 0.9792 1.0231 0.9781 0.9634 260.9921 1.0381 1.0595 0.9889 1.0206 1.0489 27 1.0388 0.9775 0.9344 0.96960.9725 0.8906 28 1.0985 1.0231 1.0326 1.1254 1.0628 1.1204

In a third embodiment, the functional model for TBS calculation is:TBS=F(R), with a specific form shown as follows:

${TBS} = {{{function}\left( \frac{{function}\left( {Q_{m} \times R \times v \times Y \times N_{PRB}^{XL}} \right)}{\delta} \right)} \times {\delta.}}$

In the above formula, the code rate R is a function of (a) the number ofPRBs allocated for the downlink or uplink, and (b) the order of themodulation and coding Q_(m); function(•) indicates rounding, roundingup, rounding down, or retaining the original value; Y is the quantizedvalue of X that is the number of REs per PRB; δ is the quantization stepof the TBS. The modification on the code rate R or the spectrumefficiency SE is mainly to improve the link stability when the PRB issmall and the order of the MCS is low. The modified value of R or SE canbe determined according to the following two situations.

In a first situation, when the number of PRBs is small, or themodulation order of MCS is low, or the modulation order of MCS is highbut at the SE overlap (where the SE value does not change from an MCSindex to an adjacent MCS index in the MCS table), the code rate R orspectrum efficiency SE in the MCS table is corrected to obtain R′ orSE′. In this case, R′ or SE′ is used to calculate the code rate orspectrum efficiency of the TBS. For example, when the I_(MCS) in thedownlink 64 QAM MCS table is 0˜17, the value of R′ may be {0.1064,0.1387, 0.1816, 0.2227,0.2734, 0.3359, 0.3984, 0.4668, 0.5342, 0.6025,0.3018, 0.3359, 0.3857, 0.4346, 0.4912, 0.5469, 0.6055, 0.4033}, or thevalue of SE′ may be {0.2131, 0.2779, 0.3627, 0.4448, 0.5469, 0.6721,0.7973, 0.9331, 1.0689, 1.2056, 1.2056, 1.3424, 1.5412, 1.7401, 1.9638,2.1818, 2.42, 2.42}. In a second situation, when the number of PRBs islarge, or the MCS modulation order is high but not at the SE overlap(where the SE value does not change from an MCS index to an adjacent MCSindex in the MCS table), the corresponding code rate R in the MCS tableis used to calculate the TBS.

The functional model of the code rate R is shown below:

$R = \left\{ {\begin{matrix}R^{\prime} & {{N_{PRB}^{XL} \leq x},{{({or})Q_{m}} \in {S_{{lower}\; \_ \; {MCS}}\bigcup S_{{overlappingSE}\; \_ \; {high}\; \_ \; {higherMCS}}}},} \\R & {{else}.}\end{matrix}.} \right.$

The functional model of the spectral efficiency SE is shown below:

${SE} = \left\{ {\begin{matrix}{SE}^{\prime} & {{N_{PRB}^{XL} \leq x},{{({or})Q_{m}} \in {S_{{lower}\; \_ \; {MCS}}\bigcup S_{{overlappingSE}\; \_ \; {high}\; \_ \; {higherMCS}}}},} \\{SE} & {{else}.}\end{matrix}.} \right.$

Here, x is the number of PRBs allocated, for example, x has a value of6.

According to one example, the values of code rate and spectralefficiency are set in the following table, for a downlink 64 QAM:

Modu- MCS lation Index Order CodeRate*1024 I_(MCS) Q_(m) CodeRate*1024 RR′ SE SE′ 0 2 120 109 0.2344 0.2131 1 2 157 142 0.3057 0.2779 2 2 193186 0.377 0.3627 3 2 251 228 0.4893 0.4448 4 2 308 280 0.6016 0.5469 5 2379 344 0.7393 0.6721 6 2 449 408 0.877 0.7973 7 2 526 478 1.0264 0.93318 2 602 547 1.1758 1.0689 9 2 679 617 1.3262 1.2056 10 4 340 309 1.32621.2056 11 4 378 344 1.4766 1.3424 12 4 434 395 1.69535 1.5412 13 4 490445 1.9141 1.7401 14 4 553 503 2.1602 1.9638 15 4 616 560 2.4063 2.187516 4 658 620 2.5684 2.42 17 6 438 413 2.5684 2.42 18 6 466 466 2.73052.7305 19 6 517 517 3.0264 3.0264 20 6 567 567 3.3223 3.3223 21 6 616616 3.6123 3.6123 22 6 666 666 3.9023 3.9023 23 6 719 719 4.212854.21285 24 6 772 772 4.5234 4.5234 25 6 822 822 4.8193 4.8193 26 6 873873 5.1152 5.1152 27 6 910 910 5.33495 5.33495 28 6 948 948 5.55475.5547

The steps to determine TBS in this embodiment include the following:

Step 1, according to the obtained transmission parameters Q_(m), R, ν, Yand N^(XL) _(PRB), determine the value of code rate R. When the numberof PRBs is small and the MCS modulation order is low, R=R′; when thenumber of PRBs is large or the MCS modulation order is high, R=R.

Step 2, based on Q_(m)×R×ν×N_(RE), calculate and round up to obtainTBS_temp. The TBS_temp includes the transport block CRC check bits(TB_CRC).

FIG. 8A illustrates an exemplary simulation result 810 of link stabilitychanges vs. MCS index, in accordance with this embodiment. FIG. 8Autilizes deltaSNR (i.e. ΔSNR) to represent link stability with the TBScalculated and modified using the method in this embodiment to achieve atarget BLER=10%. As shown in FIG. 8A, when the MCS index is low (e.g.between 0 and 10), the deltaSNR fluctuates between 0.6 and 1.2, lessthan the fluctuation in the same MCS range shown in FIG. 1B.

FIG. 8B illustrates an exemplary simulation result 820 of SNRperformance change vs. MCS index, in accordance with this embodiment. Asshown in FIG. 8B, when the MCS index is low (e.g. between 0 and 10), theSNR curve is not so smooth as the SNR curve when the MCS index is high(e.g. between 20 and 28). As shown in FIG. 8B, given an MCS index range(e.g. between 0 and 10), the SNR curve corresponding to a lower PRB,e.g. when PRB=1, is not so smooth as the SNR curve corresponding to ahigher PRB, e.g. when PRB=6, where a smoother SNR curve indicates a morestable link.

Table 8C below shows the TBS values calculated based on a modified coderate R or modified spectral efficiency SE as in the above mentionedmethod in the third embodiment, with allocated N_(RE) ^(PRB)=132.

TABLE 8C MCS PRB Index Q_(m) 1 2 3 4 5 6 0 2 16 48 72 104 128 160 1 2 2464 96 136 168 208 2 2 32 80 128 176 224 272 3 2 48 104 168 224 280 344 42 64 136 208 280 352 424 5 2 80 168 256 344 432 520 6 2 96 200 304 408512 616 7 2 112 232 360 480 600 728 8 2 128 272 408 552 696 832 9 2 144304 464 624 784 944 10 4 144 304 464 624 784 944 11 4 168 344 520 696872 1048 12 4 192 392 600 800 1008 1208 13 4 216 448 680 904 1136 136814 4 248 504 768 1024 1288 1544 15 4 280 568 856 1144 1432 1720 16 4 304624 944 1264 1584 1904 17 6 304 624 944 1264 1584 1904 18 6 352 712 10721432 1792 2152 19 6 384 784 1184 1584 1984 2384 20 6 424 864 1304 17442184 2616 21 6 464 944 1416 1896 2376 2848 22 6 504 1016 1536 2048 25603080 23 6 544 1104 1656 2216 2768 3328 24 6 584 1184 1776 2376 2976 356825 6 624 1264 1896 2536 3168 3808 26 6 664 1336 2016 2688 3368 4032 27 6696 1400 2104 2808 3512 4208 28 6 720 1456 2184 2920 3656 4376

Table 8D below shows the simulated values of ΔSNR of adjacent MCSs, withthe TBS values calculated based on a modified code rate R or modifiedspectral efficiency SE as in the above mentioned method in the thirdembodiment, with allocated N_(RE) ^(PRB)=132, and a target BLER=10%.

TABLE 8D ΔSNR PRB I_(MCS) 1 2 3 4 5 6 0 NaN NaN NaN NaN NaN NaN 1 0.8820.9434 0.9213 0.996 1.0212 0.9661 2 0.7658 0.7567 1.0603 1.0174 1.11371.0485 3 1.1974 0.9617 1.0792 0.96 0.9327 1.0026 4 1.0352 1.0764 0.90730.9875 1.0266 0.9327 5 0.8758 0.9483 0.9703 0.9642 1.0073 1.0038 60.8268 0.835 0.9042 0.8773 0.8957 0.9178 7 0.8041 0.8154 0.9184 0.9140.9221 0.9506 8 0.6638 0.9624 0.7668 0.8405 0.8798 0.8394 9 0.7761 0.6940.7997 0.8255 0.8129 0.847 10 NaN NaN NaN NaN NaN NaN 11 0.7961 0.75890.7405 0.6579 0.6614 0.6727 12 0.7447 0.7418 0.8569 0.8696 0.8991 0.902513 0.7499 0.894 0.8251 0.7926 0.7785 0.7902 14 0.9938 0.9008 0.86920.8843 0.934 0.908 15 1.0215 0.9328 0.9152 0.9306 0.8767 0.8832 160.6453 0.784 0.853 0.904 0.9093 0.9421 17 NaN NaN NaN NaN NaN NaN 181.2379 1.1929 1.1195 1.1073 1.1307 1.0974 19 0.8761 0.8589 0.9683 0.92940.9598 0.9798 20 0.9768 1.0166 1.0144 1.0278 1.0026 0.9999 21 0.99470.992 0.9195 0.9368 0.9457 0.9483 22 0.962 0.8876 1.0037 0.9546 0.96170.9879 23 0.9928 1.1357 1.0201 1.0584 0.9959 0.9943 24 0.9511 0.94260.9596 0.9489 1.0049 0.9808 25 1.0099 1.0097 0.9852 1.0005 0.9711 1.012526 1.061 0.9384 1.0496 1.0067 1.0731 1.026 27 1.0414 1.0513 0.93980.9866 0.9268 0.9365 28 0.9567 1.0495 1.031 1.0579 1.0838 1.0464

In a fourth embodiment, after the TBS is calculated by using a formula,e.g. an existing formula or a formula according to any one of the aboveembodiments, if any one of the parameters in the formula changes, thecalculated TBS will change. For example, the parameter allocated duringthe initial pass is: Q_(m)=2, R=308/1024, the number of PRB is 2, thenumber of REs per PRB is 132, and the TBS is 120. Then the parametersallocated for retransmission are: Q_(m)=2, R=379/1024, the number of PRBis 2, the number of REs per PRB is 132, and the TBS is 176. Because thetwo calculated TBSs are different, the transmission cannot be continued.In response to this problem, in consideration that the transport blocksize is the same during initial transmission and retransmission, the TBSis quantized in this embodiment. The quantization step size increaseswhen TBS increase, which can both ensure that the TBS granularity fortransmission is good, and ensure that the TBS is the same in initialtransmission and retransmission.

The function of the quantization step is as follows:

step=2^(n), 3≤n≤10 and n is integer.

Taking the value interval of TBS (including CRC check bits) less than8448 as an example, the set of TBSs that have been verified to beuseable is [40:8:512, 528:16:1024, 1056:32:2048, 2048+64:64:6144,6144+128:128:8448]. After searching the calculated TBS, the new valueinterval is obtained as [32:8:512, 528:16:992, 1024:32:2048,2176:64:6144, 6272:128:8192]. Here, 40:8:512, for example, represents aset of values between 40 and 512, with an interval of 8. Simulationresults show that when the number of REs is 132, after calculating theintermediate TBS, it is also applicable to take the closest larger TBSfrom this interval as the actual transmitted TBS.

According to the calculated TBS, it can be known that to ensure theconsistency of the TBS in initial transmission and retransmission, thevalue of the TBS may also be constrained by the number of PRBs and theorder of MCS. That is, the quantization step may also be a function of:the number of PRBs, and/or the MCS order, and/or Spectral efficiency(SE) and/or the code rate. For example, when the number of PRBs is lessthan 3 and the order of MCS is 2, the TBS may have a fixed quantizationstep of 8; when the number of PRBs is greater than 100, the order of MCSis 6, and the code rate is greater than 8/9, the quantization step maybe 512. In this way, the scheduling range of the PRB or I_(MCS) at theinitial transmission and retransmission can be expanded, and the TBSs inthe initial transmission and the retransmission can obtain the samevalue in this range.

FIG. 9 illustrates an exemplary simulation result 910 of SNR performancechange vs. MCS index, in accordance with this embodiment. As shown inFIG. 98B, when the MCS index is low (e.g. between 0 and 10), the SNRcurve is not so smooth as the SNR curve when the MCS index is high (e.g.between 20 and 28). As shown in FIG. 9B, given an MCS index range (e.g.between 0 and 10), the SNR curve corresponding to a lower PRB, e.g. whenPRB=1, is not so smooth as the SNR curve corresponding to a higher PRB,e.g. when PRB=6, where a smoother SNR curve indicates a more stablelink.

Table 9 below shows the TBS values calculated based on a useable TBS setas in the above mentioned method in the fourth embodiment, withallocated N_(RE) ^(PRB)=132.

TABLE 9 MCS PRB Index Q_(m) 1 2 3 4 5 6 0 2 24 48 80 112 144 176 1 2 3272 112 152 192 232 2 2 40 88 136 184 240 288 3 2 56 120 184 248 312 3764 2 64 144 224 304 384 464 5 2 88 184 280 376 472 576 6 2 104 216 336448 576 688 7 2 120 256 392 528 672 800 8 2 144 296 456 608 768 928 9 2160 336 512 688 864 1040 10 4 160 336 512 688 864 1040 11 4 184 376 576768 960 1168 12 4 208 432 656 880 1104 1328 13 4 240 496 752 1008 12641520 14 4 272 560 848 1136 1424 1712 15 4 304 624 944 1264 1584 1904 164 328 672 1008 1360 1680 2032 17 6 328 672 1008 1360 1680 2032 18 6 352720 1072 1456 1808 2160 19 6 384 784 1200 1584 2000 2416 20 6 424 8641328 1744 2224 2672 21 6 464 944 1424 1904 2416 2864 22 6 512 1040 15522096 2608 3120 23 6 544 1104 1680 2224 2800 3376 24 6 592 1200 1776 24162992 3568 25 6 624 1264 1904 2544 3184 3824 26 6 672 1360 2032 2736 33764072 27 6 704 1424 2160 2864 3568 4264 28 6 720 1456 2224 2928 3696 4392

In a fifth embodiment, after the TBS is calculated by using a formula,e.g. an existing formula or a formula according to any one of the aboveembodiments, the UE or BS selects, from a quantized TBS set, a TBS thatis closest to the calculated TBS as the final TBS for transmission. Theelements {TBS_(i), i=1, 2, . . . } in the quantized TBS set satisfy atleast one of the following conditions.

In accordance with Condition 1, each element TBS_(i) satisfies: TBS_(i)mod 8=0, TBS_(i)

${{{mod}\; \left\lceil \frac{{TBS}_{i} + {TB\_ CRC}}{8448 - 24} \right\rceil} = 0},{{{{TBS}_{i}{mod}\left\lceil \frac{{TBS}_{i} + {TB\_ CRC}}{3840 - 24} \right\rceil} = 0};}$

where “X mod Y=0” means X is divisible by X.

In accordance with Condition 2, each element TBS_(i) satisfies: TBS_(i)mod 8=0, TBS_(i)

${{{mod}\; \left\lceil \frac{{TBS}_{i} + {TB\_ CRC}}{8448 - 24} \right\rceil} = 0},{{{TBS}_{i}{mod}\; \left\lceil \frac{{TBS}_{i} + {TB\_ CRC}}{3840 - 24} \right\rceil} = 0},{\left( {{TBS}_{i} + {TB\_ CRC}} \right)/\left\lceil \frac{{TBS}_{i} + {TB\_ CRC}}{8448 - 24} \right\rceil}$${{{mod}\; 8} = 0},{{{{\left( {{TBS}_{i} + {TB\_ CRC}} \right)/\left\lceil \frac{{TBS}_{i} + {TB\_ CRC}}{3840 - 24} \right\rceil}{mod}\; 8} = 0};}$

where e.g. ┌X┐ means rounding up for X.

In accordance with Condition 3, each element TBS_(i) is less than orequal to 8424, each element TBS_(i) belongs to the information bit set{24:8:496, 512:16:1008, 1040:32:2032, 2096:64:3824, 3880:64:6120,6248:128:7656, 8040, 8424}.

In accordance with Condition 4, when TBS_(i) is less than or equal to athreshold K_(threshold), (TBS_(LTE)-TBS_(NR))/TBS_(NR)<0.2; and whenTBS_(i) is greater than the threshold K_(threshold),(TBS_(LTE)-TBS_(NR))/TBS_(NR)<0.05. Here, K_(threshold) is a value fromthe range {K_(threshold)|K_(min)<K_(threshold)<K_(max)}, K_(min) is aninteger between 10 and 100, K_(max) is an integer greater than 10000.For example, K_(threshold)=1000. TBS_(LTE) is the TBS set defined for aLong Term Evolution (LTE) system; TBS_(NR) is the TBS set defined underthis embodiment, i.e. a TBS set to be defined for a NR system based oneMBB.

In accordance with Condition 5, generating a first ordered sequenceincluding integers that are between K_(min) and K_(min), and satisfyCondition 1 or Condition 2; generating a second ordered sequenceincluding integers that are between K_(min) and K_(min), and arepredefined for a LTE system; quantizing the first ordered sequenceaccording to the second ordered sequence to generate the third sequence;and the quantized set in this embodiment includes all elements in thethird sequence. K_(min) is an integer between 10 and 100, and K_(max) isan integer greater than 10000. For example, K_(threshold)=1000.

In one example, the quantization process includes the following steps.First, traverse to get a first sequence TBS Sequence^(x) satisfying theCondition 1. Then, using the LTE TBS sequence as a second sequence,compare the elements TBS_(i) ^(LTE) in the second sequence with all theelements in the first sequence TBS Sequence^(x) to find the TBS_(j) ^(x)in the first sequence that is equal to or rounding to or rounding up toor rounding down to a value TBS_(i) ^(LTE), and replace the originalelement TBS_(i) ^(LTE) with the TBS_(j) ^(x) to obtain the third TBSsequence. The quantized set of TBSs shall include at least all theelements in the third TBS Sequence.

For example, a sequence satisfying Condition 1 and including integersfrom 16 to 512 is taken as the first sequence, and all the elements inthe first sequence are as follows: {16 24 32 40 48 56 64 72 80 88 96 104112 120 128 136 144 152 160 168 176 184 192 200 208 216 224 232 240 248256 264 272 280 288 296 304 312 320 328 336 344 352 360 368 376 384 392400 408 416 424 432 440 448 456 464 472 480 488 496 504 512}. All LTETBSs from 16 to 512 form the second sequence in descending order, wherethe elements of the second sequence are as follows: {16 24 32 40 56 7288 104 120 136 144 152 176 208 224 256 280 288 296 328 336 344 376 392408 424 440 456 472 488 504}. The first sequence is quantized accordingto the second sequence, which is divided into three quantizationmethods. Each quantization method obtains a third sequence. During theprocess of obtaining the third sequence, the quantization method shouldbe consistent. For example, if the second element 24 in the secondsequence is compared with each element in the first sequence, andaccording to the closest element rule, 24 in the first sequence isquantized to be the second element in the third sequence; if the secondelement 24 in the second sequence is compared with each element in thefirst sequence, and according to the closest but larger element rule, alarger element value is quantized to obtain 32 in the first sequence asthe second element in the third sequence; if the second element 24 inthe second sequence is compared with each element in the first sequence,and according to the closest but smaller element rule, a smaller elementvalue is quantized to obtain 16 in the first sequence as the secondelement in the third sequence; and so on and so forth until the elementsin the second sequence are quantified, then three third sequences indescending order are obtained.

According to the first quantization method, the element in the firstsequence closest to the second sequence is found, and the third sequenceobtained is as follows: {16 24 32 40 56 72 88 104 120 136 144 152 176208 224 256 280 288 296 328 336 344 376 392 408 424 440 456 472 488504}. According to the second quantization method, the element in thefirst sequence that is closest and larger than the second sequence isfound, and the third sequence obtained is as follows: {24 32 40 48 56 6480 96 112 128 144 152 160 184 232 264 288 296 304 336 344 352 384 400416 432 448 464 480 496 512}. According to the third quantizationmethod, the element in the first sequence that is closest and smallerthan the element in the second sequence is found, and the third sequenceobtained is as follows: {16 24 32 40 64 80 96 112 128 136 144 168 200216 248 272 280 288 320 328 336 368 384 400 416 432 448 464 480 496}.

The set of quantized TBSs includes at least all the elements in thethird sequence. For example, if the third sequence is a set ofquantization TBSs, the resource or transmission parameters are: themodulation order Q_(m)=2, the code rate R=0.5132, the layer number is 1,the number of PRBs is 1, and the number of REs per PRB is 128, roundingup to calculate an intermediate TBS of 132, the nearest neighborrelative to the intermediate TBS is 136 (or a larger value of 136, or asmaller value of 120) is selected as a quantized TBS according to thethird sequence to be taken as the actual transmitted TBS.

In one example, suppose the third TBS sequence obtained from the firstsequence satisfy the Condition 1. When an unquantized first sequence istaken as a quantized TBS table and referred to as TBS Sequence1, thedistribution of the quantized TBS in the PDSCH 64 QAM-MCS table and acomparison with the LTE TBS table is shown in FIG. 10A. When the thirdTBS Sequence is taken as a quantized TBS table1, the distribution of thequantized TBS in the PDSCH 64 QAM-MCS table and a comparison with theLTE TBS table is shown in FIG. 10B.

In another example, suppose the third TBS sequence obtained from thefirst sequence satisfy the Condition 2. When an unquantized firstsequence is taken as a quantized TBS table and referred to as TBSSequence2, the distribution of the quantized TBS in the PDSCH 64 QAM-MCStable and a comparison with the LTE TBS table is shown in FIG. 11A. Whenthe third TBS Sequence is taken as a quantized TBS table2, thedistribution of the quantized TBS in the PDSCH 64 QAM-MCS table and acomparison with the LTE TBS table is shown in FIG. 11B.

In yet another example, suppose the third IBS sequence obtained from thefirst sequence satisfy the Condition 3. When an unquantized firstsequence is taken as a quantized TBS table and referred to as TBSSequence3, the distribution of the quantized TBS in the PDSCH 64 QAM-MCStable and a comparison with the LTE TBS table is shown in FIG. 12A. Whenthe third TBS Sequence is taken as a quantized TBS table3, thedistribution of the quantized TBS in the PDSCH 64 QAM-MCS table and acomparison with the LTE TBS table is shown in FIG. 12B.

While various embodiments of the present disclosure have been describedabove, it should be understood that they have been presented by way ofexample only, and not by way of limitation. Likewise, the variousdiagrams may depict an example architectural or configuration, which areprovided to enable persons of ordinary skill in the art to understandexemplary features and functions of the present disclosure. Such personswould understand, however, that the present disclosure is not restrictedto the illustrated example architectures or configurations, but can beimplemented using a variety of alternative architectures andconfigurations. Additionally, as would be understood by persons ofordinary skill in the art, one or more features of one embodiment can becombined with one or more features of another embodiment describedherein. Thus, the breadth and scope of the present disclosure should notbe limited by any of the above-described exemplary embodiments.

It is also understood that any reference to an element herein using adesignation such as “first,” “second,” and so forth does not generallylimit the quantity or order of those elements. Rather, thesedesignations can be used herein as a convenient means of distinguishingbetween two or more elements or instances of an element. Thus, areference to first and second elements does not mean that only twoelements can be employed, or that the first element must precede thesecond element in some manner.

Additionally, a person having ordinary skill in the art would understandthat information and signals can be represented using any of a varietyof different technologies and techniques. For example, data,instructions, commands, information, signals, bits and symbols, forexample, which may be referenced in the above description can berepresented by voltages, currents, electromagnetic waves, magneticfields or particles, optical fields or particles, or any combinationthereof.

A person of ordinary skill in the art would further appreciate that anyof the various illustrative logical blocks, modules, processors, means,circuits, methods and functions described in connection with the aspectsdisclosed herein can be implemented by electronic hardware (e.g., adigital implementation, an analog implementation, or a combination ofthe two), firmware, various forms of program or design codeincorporating instructions (which can be referred to herein, forconvenience, as “software” or a “software module), or any combination ofthese techniques.

To clearly illustrate this interchangeability of hardware, firmware andsoftware, various illustrative components, blocks, modules, circuits,and steps have been described above generally in terms of theirfunctionality. Whether such functionality is implemented as hardware,firmware or software, or a combination of these techniques, depends uponthe particular application and design constraints imposed on the overallsystem. Skilled artisans can implement the described functionality invarious ways for each particular application, but such implementationdecisions do not cause a departure from the scope of the presentdisclosure. In accordance with various embodiments, a processor, device,component, circuit, structure, machine, module, etc. can be configuredto perform one or more of the functions described herein. The term“configured to” or “configured for” as used herein with respect to aspecified operation or function refers to a processor, device,component, circuit, structure, machine, module, etc. that is physicallyconstructed, programmed and/or arranged to perform the specifiedoperation or function.

Furthermore, a person of ordinary skill in the art would understand thatvarious illustrative logical blocks, modules, devices, components andcircuits described herein can be implemented within or performed by anintegrated circuit (IC) that can include a general purpose processor, adigital signal processor (DSP), an application specific integratedcircuit (ASIC), a field programmable gate array (FPGA) or otherprogrammable logic device, or any combination thereof The logicalblocks, modules, and circuits can further include antennas and/ortransceivers to communicate with various components within the networkor within the device. A general purpose processor can be amicroprocessor, but in the alternative, the processor can be anyconventional processor, controller, or state machine. A processor canalso be implemented as a combination of computing devices, e.g., acombination of a DSP and a microprocessor, a plurality ofmicroprocessors, one or more microprocessors in conjunction with a DSPcore, or any other suitable configuration to perform the functionsdescribed herein.

If implemented in software, the functions can be stored as one or moreinstructions or code on a computer-readable medium. Thus, the steps of amethod or algorithm disclosed herein can be implemented as softwarestored on a computer-readable medium. Computer-readable media includesboth computer storage media and communication media including any mediumthat can be enabled to transfer a computer program or code from oneplace to another. A storage media can be any available media that can beaccessed by a computer. By way of example, and not limitation, suchcomputer-readable media can include RAM, ROM, EEPROM, CD-ROM or otheroptical disk storage, magnetic disk storage or other magnetic storagedevices, or any other medium that can be used to store desired programcode in the form of instructions or data structures and that can beaccessed by a computer.

In this document, the term “module” as used herein, refers to software,firmware, hardware, and any combination of these elements for performingthe associated functions described herein. Additionally, for purpose ofdiscussion, the various modules are described as discrete modules;however, as would be apparent to one of ordinary skill in the art, twoor more modules may be combined to form a single module that performsthe associated functions according embodiments of the presentdisclosure.

Additionally, memory or other storage, as well as communicationcomponents, may be employed in embodiments of the present disclosure. Itwill be appreciated that, for clarity purposes, the above descriptionhas described embodiments of the present disclosure with reference todifferent functional units and processors. However, it will be apparentthat any suitable distribution of functionality between differentfunctional units, processing logic elements or domains may be usedwithout detracting from the present disclosure. For example,functionality illustrated to be performed by separate processing logicelements, or controllers, may be performed by the same processing logicelement, or controller. Hence, references to specific functional unitsare only references to a suitable means for providing the describedfunctionality, rather than indicative of a strict logical or physicalstructure or organization.

Various modifications to the implementations described in thisdisclosure will be readily apparent to those skilled in the art, and thegeneral principles defined herein can be applied to otherimplementations without departing from the scope of this disclosure.Thus, the disclosure is not intended to be limited to theimplementations shown herein, but is to be accorded the widest scopeconsistent with the novel features and principles disclosed herein, asrecited in the claims below.

What is claimed is:
 1. A method performed by a wireless communicationdevice, the method comprising: receiving control information from awireless communication node, wherein the control information includes aplurality of transmission parameters related to transport blocks to betransmitted between the wireless communication device and the wirelesscommunication node; calculating an intermediate transport block size(TBS) for the transport blocks based on the plurality of transmissionparameters; modifying the intermediate TBS to generate a modified TBS inresponse to an event that the intermediate TBS is smaller than athreshold; and determining a final TBS for the transport blocks based ona TBS that is closest to the modified TBS, among TBSs that are in aquantized set and not smaller than the modified TBS.
 2. The method ofclaim 1, wherein the plurality of transmission parameters comprises: amodulation order configured for transmission of the transport blocks; acode rate configured for transmission of the transport blocks; and aquantity of physical resource blocks configured for transmission of thetransport blocks.
 3. The method of claim 2, wherein modifying theintermediate TBS comprises: determining a correction factor based on:the quantity of physical resource blocks, the modulation order and thecode rate; and modifying the intermediate TBS by the correction factorto generate the modified TBS.
 4. The method of claim 2, whereincalculating the intermediate TBS comprises: calculating a multiplicationproduct of: the modulation order, the code rate, the quantity ofphysical resource blocks, and a quantity of layers configured fortransmission of the transport blocks; and using the multiplicationproduct as the intermediate TBS.
 5. The method of claim 1, whereinmodifying the intermediate TBS comprises: dividing the intermediate TBSby a quantization step that is equal to a power of two to generate aquotient; rounding down the quotient to generate a first integer;multiplying the first integer by the quantization step to generate asecond integer; and generating the modified TBS based on the secondinteger.
 6. A method performed by a wireless communication node, themethod comprising: generating a plurality of transmission parametersrelated to transport blocks; transmitting control information thatcomprises the plurality of transmission parameters; calculating anintermediate transport block size (TBS) for the transport blocks basedon the plurality of transmission parameters; modifying the intermediateTBS to generate a modified TBS in response to an event that theintermediate TBS is smaller than a threshold; determining a final TBSfor the transport blocks based on a TBS that is closest to the modifiedTBS, among TBSs that are in a quantized set and not smaller than themodified TBS; and communicating with a wireless communication deviceusing the transport blocks based on the final TBS.
 7. The method ofclaim 6, wherein the plurality of transmission parameters comprises: amodulation order configured for transmission of the transport blocks; acode rate configured for transmission of the transport blocks; and aquantity of physical resource blocks configured for transmission of thetransport blocks.
 8. The method of claim 7, wherein modifying theintermediate TBS comprises: determining a correction factor based on:the quantity of physical resource blocks, the modulation order and thecode rate; and modifying the intermediate TBS by the correction factorto generate the modified TBS.
 9. The method of claim 7, whereincalculating the intermediate TBS comprises: calculating a multiplicationproduct of: the modulation order, the code rate, the quantity ofphysical resource blocks, and a quantity of layers configured fortransmission of the transport blocks; and using the multiplicationproduct as the intermediate TBS.
 10. The method of claim 6, whereinmodifying the intermediate TBS comprises: dividing the intermediate TBSby a quantization step that is equal to a power of two to generate aquotient; rounding down the quotient to generate a first integer;multiplying the first integer by the quantization step to generate asecond integer; and generating the modified TBS based on the secondinteger.
 11. A first communication apparatus comprising a processor anda memory, wherein the memory stores instructions that, when executed,causes the processor to implement a method recited in any of claims 1 to5.
 12. A first communication apparatus comprising a processor and amemory, wherein the memory stores instructions that, when executed,causes the processor to implement a method recited in any of claims 6 to10.
 13. A non-transitory computer-readable medium havingcomputer-executable instructions stored thereon, the computer-executableinstructions, when executed by a processor, causing the processor toimplement a method recited in any of claims 1 to 10.